About

I am Charin Modchang, a physicist and infectious disease modeler at Mahidol University, where I lead the Medical Biophysics & Disease Modeling Group in the Department of Physics, Faculty of Science. My work sits at the intersection of physics, mathematics, computer science, and public health, with a central goal: to use quantitative models and AI to better understand, anticipate, and control infectious diseases.

My research centers on the transmission dynamics of infectious diseases — from directly transmitted respiratory infections, to vector-borne diseases such as dengue and other mosquito-borne infections, to zoonoses that jump between animals and humans. I develop and analyze models ranging from mechanistic compartmental frameworks to machine-learning and neural-mechanistic hybrids, to examine how infections spread through populations and how interventions — vaccination, vector control, behavioral measures, or policy changes — can alter those dynamics over time and across regions. A substantial part of this work involves extracting insight from disease surveillance data, including both routine clinical reporting and wastewater-based epidemiology, to support data-informed decision-making, especially in low- and middle-income settings.

Alongside the disease modeling work, I also maintain a research thread in computational biomechanics, using finite-element modeling — and, increasingly, AI-assisted design — to study microneedle systems for transdermal drug and vaccine delivery. It is a complementary line of work that applies physics, computation, and machine learning to health challenges at a very different scale.

I serve on the editorial boards of Scientific Reports, BMC Infectious Diseases, and PLOS Global Public Health, and contribute regularly to peer review at the interface of quantitative science and public health. Recent recognition of this work includes being named a Mahidol University Top 1% Researcher in 2023 and receiving the MUSC Outstanding Researcher Award in 2025.

Teaching and mentoring are central to my work. I supervise graduate students and early-career researchers interested in mathematical modeling, AI for health, and the physics of complex biological systems, and I teach machine learning to PhD students. I particularly enjoy working with interdisciplinary teams — clinicians, epidemiologists, public health officers, and data scientists — to tackle problems that matter for health in Thailand and the wider region.

If you are interested in collaboration, supervision, or learning more about my work, please explore my publications, download my CV, or find me on my Mahidol University profile.